Claude Opus 4.1 vs YOLO World

Compare Claude Opus 4.1 and YOLO World side-by-side. See how these vision models stack up in Object Detection.

Compare Claude Opus 4.1 vs YOLO World live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Detect and compare bounding boxes across models on the same image.

Open Object Detection in the full playground
AnthropicClaude Opus 4.1
Run to compare this model.
TencentYOLO World
Run to compare this model.

Models in this comparison

Tencent

Claude Opus 4.1 vs YOLO World: Overview

Claude Opus 4.1

Claude 4.1 Opus, released by Anthropic in August 2025, is the upgraded flagship of the Claude 4 family, building on Opus 4 with stronger reasoning and agentic capabilities. Like its predecessor, it is multimodal and optimized for text, code, and tool use, with support for large context windows suited to multi-file codebases, technical workflows, and long-horizon problem solving.

On benchmarks, Opus 4.1 improves coding performance, reaching ~74.5% on SWE-Bench Verified compared to Opus 4’s ~72.5%. It demonstrates more precise debugging, refactoring, and orchestration of agentic tasks while maintaining similar safety and alignment safeguards. It is best suited for enterprise-scale software development, research automation, and advanced reasoning workflows where reliability and depth of analysis are critical.

YOLO World

YOLO-World v2 Small (YOLO-World-S-v2) is the smallest variant of Tencent AI Lab’s YOLO-World v2 family, released around February 2024 under GPL-v3. With ~13 million parameters, it adopts a prompt-then-detect paradigm using offline vocabularies and is pretrained on large-scale datasets such as Objects365 and GoldG. The model processes image inputs at 640×640 or 1280×1280 resolutions and supports zero-shot open-vocabulary object detection, enabling recognition of novel categories from text prompts without retraining.

Evaluations show competitive results across benchmarks like LVIS and COCO, while maintaining real-time efficiency. On an NVIDIA V100, the small variant reaches ~74 FPS at standard resolutions. Together with larger YOLO-World v2 models, it provides a scalable framework for efficient, open-vocabulary detection across diverse deployment settings.

Claude Opus 4.1 vs YOLO World Comparison Table

PropertyClaude Opus 4.1YOLO World
OrganizationAnthropicTencent AI Lab
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateAug 2025Feb 2024
Context Window200K13.0M
Parameters
LicenseProprietaryGPL v3
Pricing per 1M tokens
Input $/1M$15.00
Output $/1M$75.00
Vision Tasks
Object DetectionDemoDemo
CaptioningDemo
ClassificationDemo
OCRDemo
Open Vocabulary Object Detection
Phrase Grounding
Vision Language
Visual Question AnsweringDemo
Model Features
Multimodal Vision
Foundation Vision
LLMs with Vision Capabilities
Real-Time Vision
Zero-shot Detection
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
59.7%
Avg Response Time7.09s
Median input tokensincl. image tokens2.0K
Median output tokens140
Est. cost / taskon this benchmark$0.040
Defect Detection
73.3%(11/15)
Document Understanding
88.9%(8/9)
Object Counting
0%(0/10)
Object Understanding
64.3%(9/14)
Spatial Understanding
63.2%(12/19)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology